REU Site: Mathematical, Statistical, and Computational Methods in the Life Sciences

REU 网站:生命科学中的数学、统计和计算方法

基本信息

  • 批准号:
    2050133
  • 负责人:
  • 金额:
    $ 27.56万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-04-01 至 2024-03-31
  • 项目状态:
    已结题

项目摘要

The REU program Mathematical, Statistical, and Computational Methods in the Life Sciences is an eight-week intensive program that actively engages undergraduate students in research projects designed to introduce them to mathematical, statistical, and computational methods that are used in the study of life science questions. Students work individually or in groups of two or three, under the supervision and guidance of three faculty mentors. The research projects cover a wide array of life science applications on the dynamics of populations, epidemics, organisms, cells, and proteins. The objectives of the program are to engage undergraduate students, especially those from underrepresented groups and from academic institutions with limited STEM research opportunities, in innovative research projects, to expose them to active research environments, and to provide them with the necessary technical skills to do independent research. Through a series of educational and social activities, REU participants have opportunities to enhance their professional development and to form a network of partners among the participants and collaborators in the program. Faculty continue to mentor the REU participants after the 8-week program to guide them in writing their results for publication and to assist them as they transition into graduate school. The goal of the program is to motivate and to inspire the REU participants to continue graduate study in mathematics, statistics, or a related field and to pursue academic or other research careers in STEM disciplines.The research projects of the REU program introduce undergraduate students to mathematical, statistical, and computational methods that enable them to pursue independent research on current questions in the life sciences. Under the guidance of experienced faculty mentors, the student research projects will involve (1) development of new stochastic models and computational methods to address biological questions on emerging diseases or species invasion; (2) new methods in time-nonhomogeneous processes to determine times at which zoonotic transmission risk is greatest; (3) development of numerical methods, especially the primal-dual weak Galerkin finite element methods, with applications in Nernst-Planck model arising from life sciences; (4) development of optimization methods with the mathematical and statistical constraints inherent to the biological and chemical aspects of the structural alignment of protein binding sites; and (5) new insights on the effect of community structure and nutrient cycling when aquatic food webs are subject to stoichiometric constraints. The research projects will build on current results and aim to contribute to new mathematical, statistical, and computational methods, algorithm design, analysis, data collection, and implementation to address important complex problems in the life sciences. The results from the research projects will be disseminated through student participation in conferences and workshops, and through publications in mathematical, statistical, and biological journals. In addition, code packages that are developed will be available on the program's website.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
REU计划生命科学中的数学、统计和计算方法是一个为期八周的密集课程,旨在让本科生积极参与旨在向他们介绍用于研究生命科学问题的数学、统计和计算方法的研究项目。学生在三名教师导师的监督和指导下,单独或以两人或三人为一组进行学习。这些研究项目涵盖了广泛的生命科学应用,涉及种群、流行病、生物体、细胞和蛋白质的动态。该计划的目标是让本科生,特别是那些来自代表性不足的群体和来自STEM研究机会有限的学术机构的本科生,参与创新研究项目,让他们接触到活跃的研究环境,并为他们提供进行独立研究所需的技术技能。通过一系列的教育和社会活动,REU参与者有机会提高他们的专业发展,并在计划的参与者和合作者中形成一个合作伙伴网络。在为期8周的课程结束后,教职员工继续指导REU的参与者,指导他们撰写结果以供发表,并在他们过渡到研究生院时帮助他们。该计划的目标是激励和激励REU参与者继续在数学、统计学或相关领域的研究生学习,并在STEM学科中追求学术或其他研究生涯。REU计划的研究项目向本科生介绍数学、统计和计算方法,使他们能够对当前生命科学中的问题进行独立研究。在经验丰富的教师的指导下,学生的研究项目将包括:(1)开发新的随机模型和计算方法,以解决新出现的疾病或物种入侵的生物学问题;(2)在时间非均匀过程中确定人畜共患病传播风险最大的时间的新方法;(3)开发数值方法,特别是原始-对偶弱Galerkin有限元方法,应用于生命科学产生的Nernst-Planck模型;(4)开发具有蛋白质结合位点结构比对的生物和化学方面固有的数学和统计约束的优化方法;以及(5)当水生食物网受到化学计量限制时,对群落结构和营养循环的影响的新见解。这些研究项目将建立在现有成果的基础上,旨在促进新的数学、统计和计算方法、算法设计、分析、数据收集和实施,以解决生命科学中的重要复杂问题。研究项目的结果将通过学生参加会议和研讨会,以及通过在数学、统计和生物期刊上发表文章来传播。此外,开发的代码包将在该计划的网站上提供。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Active learning based sampling for high-dimensional nonlinear partial differential equations
基于主动学习的高维非线性偏微分方程采样
  • DOI:
    10.1016/j.jcp.2022.111848
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    4.1
  • 作者:
    Gao, Wenhan;Wang, Chunmei
  • 通讯作者:
    Wang, Chunmei
Lyme Disease Models of Tick-Mouse Dynamics with Seasonal Variation in Births, Deaths, and Tick Feeding
  • DOI:
    10.1007/s11538-023-01248-y
  • 发表时间:
    2024-03-01
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Husar,Kateryna;Pittman,Dana C.;Allen,Linda J. S.
  • 通讯作者:
    Allen,Linda J. S.
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Leif Ellingson其他文献

Nonparametric estimation of means on Hilbert manifolds and extrinsic analysis of mean shapes of contours
希尔伯特流形均值的非参数估计和轮廓平均形状的外在分析
  • DOI:
  • 发表时间:
    2013
  • 期刊:
  • 影响因子:
    1.6
  • 作者:
    Leif Ellingson;V. Patrangenaru;F. Ruymgaart
  • 通讯作者:
    F. Ruymgaart
The Cholesky normal distribution for SPD matrices and inference for the mean
  • DOI:
    10.1007/s00362-024-01640-3
  • 发表时间:
    2024-12-15
  • 期刊:
  • 影响因子:
    1.100
  • 作者:
    Benoit Ahanda;Leif Ellingson;Daniel E. Osborne
  • 通讯作者:
    Daniel E. Osborne
Regression models using the LINEX loss to predict lower bounds for the number of points for approximating planar contour shapes
使用 LINEX 损失来预测近似平面轮廓形状的点数下限的回归模型
  • DOI:
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    1.5
  • 作者:
    J. M. T. Jayasinghe;Leif Ellingson;Chalani C. Prematilake
  • 通讯作者:
    Chalani C. Prematilake
On the CLT on Low Dimensional Stratified Spaces
低维分层空间上的CLT
  • DOI:
    10.1007/978-1-4939-0569-0_21
  • 发表时间:
    2014
  • 期刊:
  • 影响因子:
    5
  • 作者:
    Leif Ellingson;H. Hendriks;V. Patrangenaru;Paul San Valentin
  • 通讯作者:
    Paul San Valentin
Robustness of lognormal confidence regions for means of symmetric positive definite matrices when applied to mixtures of lognormal distributions
应用于对数正态分布混合时对称正定矩阵均值的对数正态置信区域的稳健性
  • DOI:
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0.8
  • 作者:
    Benoit Ahanda;D. Osborne;Leif Ellingson
  • 通讯作者:
    Leif Ellingson

Leif Ellingson的其他文献

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